Browse Articles

Regional disparities in cerebral perfusion and brain tissue microstructure damage in adult patients with Moyamoya syndrome

Abstract In Moyamoya syndrome (MMS), cerebral perfusion and tissue microstructure are impaired, but regional differences remain unclear. This study analyzed 22 adult MMS patients using CT perfusion (CTP) and intravoxel incoherent motion (IVIM). All hemispheres were classified into four ischemia grades based on symptoms and imaging. CTP parameters (CBF, CBV, MTT, TTP) and IVIM parameters (ADC, D, D*, f) were measured in the temporal lobe and basal ganglia. The relative values of CTP parameters and absolute values of IVIM parameters were compared across hemispheres with different ischemia grades. Additionally, correlation analyses were conducted between CTP and IVIM parameters. Results showed that in the temporal lobe, rMTT and rTTP were significantly increased ( p  = 0.018 and 0.002, respectively) with higher ischemia grades, while basal ganglia changes were similar but milder, with only rTTP delay being significant ( p  = 0.011). IVIM analysis revealed significantly elevated ADC values in association with higher ischemia grades (overall p  = 0.011). Additionally, significant variations were observed in both D* (overall p  = 0.041) and the perfusion fraction f (overall p  = 0.043). In the basal ganglia, IVIM parameters showed no significant differences across ischemia grades. Weak or insignificant correlations were found between IVIM parameters and CTP parameters. The study suggested that perfusion and microstructural damage in the basal ganglia were less severe than in the temporal lobe, and that IVIM offers insights into microvascular status that are complementary to those from hemodynamic perfusion imaging.

Fuzzy-fractional modeling of cholera disease using real outbreak data of angola in caputo-TFN framework

Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia

Investigating the impact of PVC microplastics on membrane fouling behavior in MBR for enhanced wastewater treatment efficiency

Computational identification of potential antifungal targets against Claviceps purpurea via MD simulation and MM/GBSA

Treadmill exercise alleviates depression in female mice induced by chronic unpredictable mild stress through the Inhibition of cGAS-STING signalling

Short-term impacts of cold front passage on coastal water quality and material transport

Lightweight XOR-based visual cryptography using random shares for secure colour image sharing with minimal shares

Abstract In the current digital environment, safeguarding visual data from unauthorized use remains a substantial challenge. Sensitive imagery, including biometric, medical and defence images, represents a frequent target of destructive cyberattacks. Although conventional visual cryptography approaches achieve satisfactory results in rendering visual content unreadable, these schemes often present serious drawbacks that include excessive computation, pixel expansion and reduced reconstruction quality. This paper suggests a new method and concept of lightweight visual cryptography based on the use of bitwise operations (specifically XOR) for secured colour image sharing. This methodology employs three non-expansible shares while providing the user with lossless encryption and low computation in addition to strong statistical and differential attack resistance during encryption and decryption. The proposed method utilizes a cryptographically secure pseudo-random number generator (CSPRNG) and reversible XOR bitwise operations to determine and generate three unique unreadable shares. Tests and experiments reveal that the resulting shares have high reconstruction quality (PSNR > 40 dB), an ideal degree of randomness (entropy ≈ 7.997) and tolerable processing time (in comparison to traditional XOR-, polynomial- and CRT- based visual cryptography schemes). The new method and concept emphasize the merging of simplicity, scalability, and robustness in a computationally sound and secure solution for real-time use in areas such as military imaging, biometric authentication, and multi-media communication.

C─H Amination of Polypropylene with Sodium <i>N</i> ‐Chloro‐Amides

Abstract Polypropylene (PP) is one of the most produced polymers. To meet the requirements of many modern technologies, it is very urgent to introduce diverse functional groups onto PP. Selective C─N bonds forming via C─H functionalization have been considered as a universal platform; however, it remains a significant challenge. Herein, we report a mild, catalyst‐free, and light‐free C─H amination of both commodity and postconsumer PP using sodium N ‐chloro‐amides as nitrogen sources. This method allows the efficient preparation of a variety of aminated PP materials (up to 2.4 mol% LOF) via direct functionalizations and subsequent functional group transformations. These aminated materials retain crystallinity and molecular weight while exhibiting new properties not present in virgin PP, such as improved compatibility in mixed plastic blends, enhanced adhesion to metals, and fluorescence properties. This work also provides a sustainable strategy to expand the use of PP waste.

Machine learning-based prediction of surface quality and tool performance in the grinding of inconel 800

Abstract This study investigates the surface grinding behavior of Inconel 800, a nickel-based superalloy widely used in high-temperature applications. Grinding tests were performed using green silicon carbide and aluminium oxide wheels under constant parameters: 2800 RPM spindle speed, 0.1 mm depth of cut, and 3.5 mm feed rate, with bio-based coolant. Surface roughness was monitored after every two passes, along with corresponding thermal imaging and wheel surface analysis. Results showed that the green silicon carbide wheel maintained better thermal stability and wear resistance, with surface roughness rising from &lt;0.3 µm to &gt;0.85 µm by the 22 nd pass. In contrast, the aluminium oxide wheel delivered a finer initial finish but wore more rapidly due to heat buildup. Manually annotated particle accumulation data enabled the development of machine learning models for tool wear prediction, with Random Forest Regression achieving the highest accuracy (R 2 &gt;0.9). The findings highlight the effectiveness of combining thermal and surface data with predictive modeling to optimize grinding performance and tool life in machining Inconel 800.

Direct SpoIIQ-SpoIIIAH interaction is dispensable for sporulation in Bacillus subtilis

Thioredoxin and tetraspanin 30 (CD63) as potential biomarkers for angioinvasion in papillary thyroid cancer

Endophilin–lamellipodin–VASP, key components in fast endophilin–mediated endocytosis, control actin polymerization within liquid-like condensates

Techno-economic and environmental evaluations of a solar thermal-assisted chiller facility in hot desert climates

Upregulation of miR-361-5p attenuates MPP+-induced neurotoxicity in dopaminergic SH-SY5Y cells as Parkinson's disease model

Carbon sequestration and tourist land use dynamics: Understanding the effects of urbanization and afforestation 

Elongator is required for pattern recognition receptor and type I interferon signaling in macrophages

Diagnostic significance of gut Microbiome dysbiosis and biomarker expression in Egyptians with hepatocellular carcinoma

Abstract Egypt has the greatest incidence of hepatitis C virus (HCV) infection globally, which is a considerable trigger of fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The gut microbiome has been recognized for contributing to various hepatic conditions. Nevertheless, its correlation with HCV and HCC is not well understood. Our study is conducted to investigate the potential relevance of some biomarkers: matrix metalloproteinase 9 (MMP9), Signal transducer and activator of transcription 3 (STAT3), superoxide dismutase (SOD), vascular endothelial growth factor (VEGF), and nuclear factor-κB (NF-κB), along with gut microbial variations, for the differentiation between HCV-related cirrhosis and HCC. The 90 fecal and blood samples were collected from 30 healthy controls, 30 HCV-related cirrhosis, and 30 HCC for detecting gut microbial abundance and biochemical markers examination. Our findings displayed the existence of intestinal microbiome dysbiosis with marked enrichment of specific species, including Bifidobacterium , Fusobacterium , Providencia , E. faecium , and Pseudomonas aeruginosa in HCC patients. Furthermore, the most enriched genera in HCV-related cirrhosis patients were Bifidobacterium , Porphyromonas , and Bacteroides . MMP9 exhibited the highest diagnostic performance of the five measured biomarkers, discriminating against HCC vs. HCV-related cirrhosis with specificity and sensitivity of 100% and 90%, respectively, at a cut-off value &gt; 166.8. Additionally, SOD and NF-κB were statistically significant discriminators of HCC from cirrhosis at cutoff values of ≤ 0.197 and &gt; 166.8. A significant correlation between microbiome abundance and VEGF and MMP9 was observed. This study illustrated that gut microbiomes contribute to HCC and HCV-related cirrhosis pathogenesis, opening approaches for cancer management and prevention.

Transmembrane BAX inhibitor motif containing 1 inhibition of lysosomal degradation of TGF-β receptor 1 suppresses cellular senescence and hepatocarcinogenesis

Unraveling high-efficiency lead-free perovskite solar cells using a CsSnGeI3/CsGeI3 dual absorber and a Cu2O HTL